The definition of conditional probability yields the following result,

The Multiplication Rule

  • This rule is important because it is often the case that
    • is desired,
    • whereas both and can be obtained from the problem description.
  • Consideration of gives

EX 2.27 blood type

  • The multiplication rule is most useful when
    • the experiment consists of several stages in succession.
  • The conditioning event then describes the outcome of the first stage
    • and the outcome of the second,
    • so that (conditioning on what occurs first) will often be known.
  • The rule is easily extended to experiments involving more than two stages.

Example

Consider three events , , and .

  • The triple intersection of these events can be represented as the double intersection .
  • Applying our previous multiplication rule to this intersection
  • and then to gives

\begin{align} &P\left( {{A}{1} \cap {A}{2} \cap {A}{3}}\right) \ = &P\left( {{A}{3} \mid {A}{1} \cap {A}{2}}\right) \cdot P\left( {{A}{1} \cap {A}{2}}\right) \ = &P\left( {{A}{3} \mid {A}{1} \cap {A}{2}}\right) \cdot P\left( {{A}{2} \mid {A}{1}}\right) \cdot P\left( {A}{1}\right) \end{align}

EX 2.28 blood type again

Remark

  • When the experiment of interest consists of a sequence of several stages,
    • it is convenient to represent these with a tree diagram.
  • Once we have an appropriate tree diagram,
    • probabilities and conditional probabilities can be entered on the various branches;
  • this will make repeated use of the multiplication rule quite straightforward.

EX 2.29